Highway passenger travel demand forecasting provides an important basis for travel planning. Considering the relationships among travel modes (highway, railway, and aviation) is necessary to accurately predict travel demand. On the basis of such relationships, influencing factors, including population, gross regional product, highway kilometers, high-speed rail construction, and aviation facility accessibility, are selected to construct a dummy variable model for forecasting highway passenger travel demand. On the basis of the chosen dummy variables (high-speed rail construction and aviation facility accessibility), model formation includes the following four conditions: no high-speed rail construction and low aviation facility accessibility; high-speed rail construction and low aviation facility accessibility; no high-speed rail construction and high aviation facility accessibility; and high-speed rail construction and high aviation facility accessibility. We measure these conditions using panel data at the city and provincial levels of China for the years 2000–2014. The error analysis between the forecasting results and accurate data collection at the National Bureau of Statistics of China verify that the model formation is correct. Results show the travel demand differences under various conditions. The elasticity coefficients among the influencing factors of travel demand explain the co-opetition relationships among travel modes. These results provide valuable guidance to the sustainable development of a passenger transportation system.


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    Title :

    Highway Passenger Travel Demand Forecasting Incorporating Relationships among Travel Modes


    Contributors:
    He, Nan (author) / Li, Ji-tao (author)


    Publication date :

    2018-09-01


    Size :

    72018-01-01 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Passenger travel demand forecasting

    National Research Council, Transportation Research Board, USA | TIBKAT | 1976